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  4. MLgsc: A Maximum-Likelihood General Sequence Classifier
 
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MLgsc: A Maximum-Likelihood General Sequence Classifier

Auteur(s)
Junier, Thomas
Herve, Vincent 
Institut de biologie 
Wunderlin, Tina 
Institut de biologie 
Junier, Pilar 
Institut de biologie 
Date de parution
2015
In
PLoS One
Vol.
7
No
10
Mots-clés
  • Databases
  • Genetic
  • Databases
  • Protein
  • *Likelihood Functions
  • Nucleotides/chemistry
  • *Phylogeny
  • Proteins/chemistry
  • Software
  • Databases

  • Genetic

  • Databases

  • Protein

  • *Likelihood Functions...

  • Nucleotides/chemistry...

  • *Phylogeny

  • Proteins/chemistry

  • Software

Résumé
We present software package for classifying protein or nucleotide sequences to user-specified sets of reference sequences. The software trains a model using a multiple sequence alignment and a phylogenetic tree, both supplied by the user. The latter is used to guide model construction and as a decision tree to speed up the classification process. The software was evaluated on all the 16S rRNA gene sequences of the reference dataset found in the GreenGenes database. On this dataset, the software was shown to achieve an error rate of around 1% at genus level. Examples of applications based on the nitrogenase subunit NifH gene and a protein-coding gene found in endospore-forming Firmicutes is also presented. The programs in the package have a simple, straightforward command-line interface for the Unix shell, and are free and open-source. The package has minimal dependencies and thus can be easily integrated in command-line based classification pipelines.
Identifiants
https://libra.unine.ch/handle/123456789/24541
Type de publication
journal article
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